ProfileFoundry: A Synthetic Person-Object Substrate for Privacy, Memory, and Tool-Use Evaluation in LLM Agent

arXiv:2606.26403 · cs.CL · Submitted 2026-06-24 · Read on arXiv

cs.CL

Submitted: 2026-06-24

Updated: 2026-08-28

Code: https://github.com/selvamsriram/ProfileFoundry

Terminology

• Provenance — 22× in this paper · explained in 4 episodes
• Consistency — 17× in this paper · explained in 3 episodes
• Benchmark — 16× in this paper · explained in 2 episodes
• Personalization — 7× in this paper · explained in 2 episodes
• Differentially Private — 4× in this paper · explained in 3 episodes
• Fidelity — 4× in this paper · explained in 2 episodes
• Trace — 4× in this paper · explained in 2 episodes
• Verifier — 4× in this paper · explained in 2 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Core — 3× in this paper · explained in 2 episodes
• Benchmarking — 2× in this paper · explained in 3 episodes
• Data Provenance — 2× in this paper · explained in 2 episodes
• Differential Privacy — 2× in this paper · explained in 4 episodes
• Grounding — 2× in this paper · explained in 3 episodes
• Temporal Reasoning — 2× in this paper · explained in 2 episodes
• Temporal consistency — 2× in this paper · explained in 2 episodes
• Abstention — 1× in this paper · explained in 1 episode
• Abstraction — 1× in this paper · explained in 1 episode
• Accountability — 1× in this paper · explained in 2 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Sparsity — 1× in this paper · explained in 4 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• Scaling Synthetic Data Creation with 1,000,000,000 Personas
• PIIBench: A Unified Multi-Source Benchmark Corpus for Personally Identifiable Information Detection
• Privasis: Synthesizing the Largest "Public" Private Dataset from Scratch
• LaMP: When Large Language Models Meet Personalization
• PersonaBench: Evaluating AI Models on Understanding Personal Information through Accessing (Synthetic) Private User Data
• LongMemEval: Benchmarking Chat Assistants on Long-Term Interactive Memory

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